Question 1

Which of the following is an example of a nonlinear regression model?

Accepted Answer

A) A quadratic regression equation 
B) A logarithmic regression equation 
C) Constant elasticity equation 
D) All of these choices 
A) A quadratic regression equation 
B) A logarithmic regression equation 
C) Constant elasticity equation 
D) All of these choices

Question 2

The standard error of the estimate (   )is essentially the

Accepted Answer

A) mean of the residuals. 
B) standard deviation of the residuals. 
C) mean of the explanatory variable. 
D) standard deviation of the explanatory variable. 
A) mean of the residuals. 
B) standard deviation of the residuals. 
C) mean of the explanatory variable. 
D) standard deviation of the explanatory variable.

Question 3

Regression analysis asks

Accepted Answer

A) if there are differences between distinct populations. 
B) if the sample is representative of the population. 
C) how a single variable depends on other relevant variables. 
D) how several variables depend on each other. 
A) if there are differences between distinct populations. 
B) if the sample is representative of the population. 
C) how a single variable depends on other relevant variables. 
D) how several variables depend on each other.

Question 4

In the multiple regression model   we interpret X1 as follows: holding X2 constant,if X1 increases by 1 unit,then the expected value of Y will increase by 9 units.

Accepted Answer

A) True 
 B)False

Question 5

The coefficients for logarithmically transformed explanatory variables should be interpreted as the percent change in the dependent variable for a 1% percent change in the explanatory variable.

Accepted Answer

A) True 
 B)False

Question 6

A regression analysis between X = sales (in $1000s)and Y = advertising ($)resulted in the following least squares line:   = 84 +7X.This implies that if there is no advertising,then the predicted amount of sales (in dollars)is $84,000.

Accepted Answer

A) True 
 B)False

Question 7

A logarithmic transformation of the response variable Y is often useful when the distribution of Y is symmetric.

Accepted Answer

A) True 
 B)False

Question 8

The adjusted R2 adjusts R2 for

Accepted Answer

A) non-linearity. 
B) outliers. 
C) low correlation. 
D) the number of explanatory variables in a multiple regression model. 
A) non-linearity. 
B) outliers. 
C) low correlation. 
D) the number of explanatory variables in a multiple regression model.

Question 9

Correlation is measured on a scale from 0 to 1,where 0 indicates no linear relationship between two variables,and 1 indicates a perfect linear relationship.

Accepted Answer

A) True 
 B)False

Question 10

When the scatterplot appears as a shapeless swarm of points,this can indicate that there is no relationship between the response variable Y and the explanatory variable X,or at least none worth pursuing.

Accepted Answer

A) True 
 B)False

Question 11

The regression line   has been fitted to the data points (28,60),(20,50),(10,18),and (25,55).The sum of the squared residuals will be

Accepted Answer

A) 20.25. 
B) 16.00. 
C) 49.00. 
D) 94.25. 
A) 20.25. 
B) 16.00. 
C) 49.00. 
D) 94.25.

Question 12

The covariance is not used as much as the correlation because

Accepted Answer

A) it is not always a valid predictor of linear relationships. 
B) it is difficult to calculate. 
C) it is difficult to interpret because it depends on the units of measurement. 
D) of all of these options. 
A) it is not always a valid predictor of linear relationships. 
B) it is difficult to calculate. 
C) it is difficult to interpret because it depends on the units of measurement. 
D) of all of these options.

Question 13

In a simple linear regression problem,suppose that   = 12.48 and   = 124.8.Then   = 0.90.

Accepted Answer

A) True 
 B)False

Question 14

In a nonlinear transformation of data,the Y variable or the X variables may be transformed,but not both.

Accepted Answer

A) True 
 B)False

Question 15

The percentage of variation (R2)ranges from

Accepted Answer

A) 0 to +1. 
B) -1 to +1. 
C) -2 to +2. 
D) -1 to 0. 
A) 0 to +1. 
B) -1 to +1. 
C) -2 to +2. 
D) -1 to 0.

Question 16

If a scatterplot of residuals shows a parabola shape,then a logarithmic transformation may be useful in obtaining a better fit.

Accepted Answer

A) True 
 B)False

Question 17

To help explain or predict the response variable in every regression study,we use one or more explanatory variables.These variables are also called response variables or independent variables.

Accepted Answer

A) True 
 B)False

Question 18

A correlation value of zero indicates _____ relationship.

Accepted Answer

A) a strong linear 
B) a weak linear 
C) no linear 
D) a perfect linear 
A) a strong linear 
B) a weak linear 
C) no linear 
D) a perfect linear

Question 19

In linear regression,a dummy variable is used to

Accepted Answer

A) represent residual variables. 
B) represent missing data in each sample. 
C) include hypothetical data in the regression equation. 
D) include categorical variables in the regression equation. 
A) represent residual variables. 
B) represent missing data in each sample. 
C) include hypothetical data in the regression equation. 
D) include categorical variables in the regression equation.

Question 20

In regression analysis,if there are several explanatory variables,it is called _____ regression.

Accepted Answer

A) simple 
B) multiple 
C) compound 
D) nonlinear 
A) simple 
B) multiple 
C) compound 
D) nonlinear

Which of the following is an example of a nonlinear regression model?

The standard error of the estimate ( )is essentially the

Regression analysis asks

In the multiple regression model we interpret X₁ as follows: holding X₂ constant,if X₁ increases by 1 unit,then the expected value of Y will increase by 9 units.

The coefficients for logarithmically transformed explanatory variables should be interpreted as the percent change in the dependent variable for a 1% percent change in the explanatory variable.

A regression analysis between X = sales (in $1000s)and Y = advertising ($)resulted in the following least squares line: = 84 +7X.This implies that if there is no advertising,then the predicted amount of sales (in dollars)is $84,000.

A logarithmic transformation of the response variable Y is often useful when the distribution of Y is symmetric.

The adjusted R² adjusts R² for

Correlation is measured on a scale from 0 to 1,where 0 indicates no linear relationship between two variables,and 1 indicates a perfect linear relationship.

When the scatterplot appears as a shapeless swarm of points,this can indicate that there is no relationship between the response variable Y and the explanatory variable X,or at least none worth pursuing.

The regression line has been fitted to the data points (28,60),(20,50),(10,18),and (25,55).The sum of the squared residuals will be

The covariance is not used as much as the correlation because

In a simple linear regression problem,suppose that = 12.48 and = 124.8.Then = 0.90.

In a nonlinear transformation of data,the Y variable or the X variables may be transformed,but not both.

The percentage of variation (R²)ranges from

If a scatterplot of residuals shows a parabola shape,then a logarithmic transformation may be useful in obtaining a better fit.

To help explain or predict the response variable in every regression study,we use one or more explanatory variables.These variables are also called response variables or independent variables.

A correlation value of zero indicates _____ relationship.

In linear regression,a dummy variable is used to

In regression analysis,if there are several explanatory variables,it is called _____ regression.

Introduction to Business Analytics

Describing the Distribution of a Variable

Finding Relationships Among Variables

Business Intelligence Bifor Data Analysis

Probability and Probability Distributions

Decision Making Under Uncertainty

Sampling and Sampling Distributions

Confidence Interval Estimation

Hypothesis Testing

Regression Analysis: Statistical Inference

Time Series Analysis and Forecasting

Introduction to Optimization Modeling

Optimization Models

Introduction to Simulation Modeling

Simulation Models

Data Mining

Analysis of Variance and Experimental Design

Statistical Process Control

Filters

Exam 10: Regression Analysis: Estimating Relationships

Which of the following is an example of a nonlinear regression model?

The standard error of the estimate ( )is essentially the

Regression analysis asks

In the multiple regression model we interpret X1 as follows: holding X2 constant,if X1 increases by 1 unit,then the expected value of Y will increase by 9 units.

The coefficients for logarithmically transformed explanatory variables should be interpreted as the percent change in the dependent variable for a 1% percent change in the explanatory variable.

A regression analysis between X = sales (in $1000s)and Y = advertising ($)resulted in the following least squares line: = 84 +7X.This implies that if there is no advertising,then the predicted amount of sales (in dollars)is $84,000.

A logarithmic transformation of the response variable Y is often useful when the distribution of Y is symmetric.

The adjusted R2 adjusts R2 for

Correlation is measured on a scale from 0 to 1,where 0 indicates no linear relationship between two variables,and 1 indicates a perfect linear relationship.

When the scatterplot appears as a shapeless swarm of points,this can indicate that there is no relationship between the response variable Y and the explanatory variable X,or at least none worth pursuing.

The regression line has been fitted to the data points (28,60),(20,50),(10,18),and (25,55).The sum of the squared residuals will be

The covariance is not used as much as the correlation because

In a simple linear regression problem,suppose that = 12.48 and = 124.8.Then = 0.90.

In a nonlinear transformation of data,the Y variable or the X variables may be transformed,but not both.

The percentage of variation (R2)ranges from

If a scatterplot of residuals shows a parabola shape,then a logarithmic transformation may be useful in obtaining a better fit.

To help explain or predict the response variable in every regression study,we use one or more explanatory variables.These variables are also called response variables or independent variables.

A correlation value of zero indicates _____ relationship.

In linear regression,a dummy variable is used to

In regression analysis,if there are several explanatory variables,it is called _____ regression.

Introduction to Business Analytics

Describing the Distribution of a Variable

Finding Relationships Among Variables

Business Intelligence Bifor Data Analysis

Probability and Probability Distributions

Decision Making Under Uncertainty

Sampling and Sampling Distributions

Confidence Interval Estimation

Hypothesis Testing

Regression Analysis: Statistical Inference

Time Series Analysis and Forecasting

Introduction to Optimization Modeling

Optimization Models

Introduction to Simulation Modeling

Simulation Models

Data Mining

Analysis of Variance and Experimental Design

Statistical Process Control

Filters

In the multiple regression model we interpret X₁ as follows: holding X₂ constant,if X₁ increases by 1 unit,then the expected value of Y will increase by 9 units.

The adjusted R² adjusts R² for

The percentage of variation (R²)ranges from